A spectrum analyzer is a device that measures the power density of an input signal and displays that power density in a form convenient to the user. A typical block diagram of a prior art spectrum analyzer is shown in FIG. 1. The spectrum analyzer of FIG. 1 includes a frequency converter 100, a low pass filter (LPF) 101, an analog-to-digital converter (ADC) 102, a processor 103, a display 104 and a control unit 105. The frequency spectrum of an applied input signal is measured in a step-by-step process. The control unit 105 controls the frequency converter 100 and, in particular, specifies at each step, a frequency band Fst . . . Fst+ΔF of the input signal spectrum that is to be currently analyzed (Fst is the start frequency of the band to be analyzed, and ΔF is the spacing between adjacent start frequencies). The frequency converter 100 transfers the band Fst . . . Fst+ΔF to the band 0 . . . ΔF. An anti-aliasing low pass filter (LPF) 101 suppresses all components with the frequencies higher than Fs/2 (where Fs is the sampling rate). The analog to digital converter (ADC) 102 transforms an incoming continuous signal into a sequence of digital samples with the sampling rate Fs. The processor 103 carries out a Fast Fourier Transform of the signal that comes from the next frequency band at each next step of the spectrum measurement. Then, processor 103 concatenates the resulting partial spectrum pieces into an aggregate spectrum of the input signal and transfers the resulting spectrum to the display 104, interacting all the time with the control unit 105.
One of the essential conditions that should be met to achieve a high measurement accuracy in a spectrum analyzer, is a requirement for the frequency converter 100 not to create spurious responses, which may substantially distort the final picture. To attain such a purpose, a conventional frequency converter usually contains several conversion stages with an appropriate selection of intermediate frequencies and frequencies of local oscillators. As an example, a prior art spectrum analyzer with a three-stage frequency converter is shown in FIG. 2.
In the spectrum analyzer of FIG. 2, the first stage of the frequency converter 100 is formed by a first mixer 200, a first band pass filter (BPF) 201 and a first local oscillator (LO) 211. The second stage of frequency converter 100 is formed by a second mixer 202, a second band pass filter 203 and a second local oscillator 212. The third stage of frequency converter 100 is formed by a third mixer 205 and a third local oscillator 213.
The first local oscillator 211 is a variable frequency oscillator with a frequency that is controlled by the control unit 105. The second local oscillator 212 and third local oscillator 213 are fixed frequency oscillators. The frequencies F1 of the first local oscillator 211, and F2 of the second local oscillator 212, are substantially higher than the frequency F3 of the third local oscillator 213.
In operation, the input signal of the spectrum analyzer of FIG. 2 is mixed with the first local signal 208 by the first mixer 200, so that signals having both sum and difference frequencies of the first local signal 208 and the input signal are produced. The first band pass filter 201 selects the difference signal creating the first intermediate frequency (IF) signal 205.
The first IF signal 205 is provided to the second mixer 202, where it is mixed with the second local signal 209. The second mixer 202 produces signals having both sum and difference frequencies of the first IF signal 205 and second local signal 209. The second band pass filter 203 selects the difference signal creating the second IF signal 206.
Similarly, the second IF signal 206 is provided to the third mixer 204 where it is mixed with the third local signal 210. The third mixer 204 produces signals having both sum and difference frequencies of the second IF signal 206 and third local signal 210. Low pass filter 101 selects the difference signal, creating ADC input signal 207.
At each next step of spectrum measurement with the start frequency Fst, control unit 105 sets the frequency F1 of the first local oscillator to equal F1=Fst+F2+F3. If the input signal has a frequency Fin, then the first IF signal 205 has a frequency F1−Fin, the second IF signal 206 has a frequency F1−Fin−F2 and the ADC input signal 207 has a frequency F3−(F1−Fin−F2)=F3−F1+Fin+F2=F3−(Fst+F2+F3)+Fin+F2=Fin−Fst. Thus, the frequency band Fst . . . Fst+ΔF of the input signal is transferred by the frequency converter 100 to the frequency band 0 . . . ΔF at the ADC input.
The frequency converter 100, shown in FIG. 2, carries out the necessary frequency transfer without producing harmful spurious components. However, in order to provide the high sensitivity and resolution for the spectrum analyzer that are needed to achieve a desired measurement accuracy, the frequency converter should possess one more quality: any phase noise that is introduced in the processed signal has to be correspondingly small.
The phase noise manifests itself as unwanted random fluctuations in a relative phase of a signal. The phase noise originates in the local oscillators of the frequency converter and finds its way into processed signal during the mixing operations. The phase noise level of a local oscillator grows when the oscillator frequency is relatively high. Therefore, the main sources of the phase noise in the block diagram of FIG. 2 are the first local oscillator 211 (especially when it includes either a yttrium-iron-garnet (YIG) transistor or a gallium-arsenide field effect transistor (GaAs FET) oscillator, as often is the case) and the second local oscillator 212. The third local oscillator 213 is usually a crystal oscillator with high frequency stability and very low level of phase noise. The phase noise of the first local oscillator 211 is θ1(t), the phase noise of the second local oscillator 212 is θ2(t), and the input signal and the third local oscillator are substantially free of phase noise. Then the phase noise of the first IF signal 205 is θ1(t), whereas phase noise of the second IF signal 206 and phase noise of the signal 207 at the ADC input is θ1(t)−θ2(t).
In the prior art, different methods of phase noise suppression are used in communication receivers, measuring devices and so on. One efficient approach consists of impressing the phase noise of a noisy oscillator onto a clean oscillator. Then during the mixing operations, phase noise of the first oscillator is added and phase noise of the second oscillator is subtracted from the processed signal phase. As a result, the output signal is free of the phase noise developed in the first oscillator. Such an approach was employed, for example, in U.S. Pat. No. 4,918,748, U.S. Pat. No. 6,313,619 and U.S. Pat. No. 6,600,906. The block diagram described in U.S. Pat. No. 6,600,906 is shown in FIG. 3. In this patent the second local oscillator 210 is supposed to have high level of phase noise. The first local oscillator 209 is taken as having a lower frequency and a small phase noise. The passage of signals in the FIG. 3 is basically the same as in first two stages of frequency converter 100 in the spectrum analyzer of FIG. 2. The distinction is that first local signal 208 is produced in FIG. 3 not by an independent local oscillator 211, but by mixing signals from the first local oscillator 211 and the second local oscillator 212 in the mixer 301 with the subsequent selection of the sum component by BPF 300. Thanks to such device structure the phase noise in the first 208 and the second 209 local signals are essentially the same. In the mixer 200 the phase noise of the first local signal is added to the processed signal and in the mixer 202 the phase noise of the second local signal is subtracted from the processed signal. Thus, in the mixer 202 a mutual cancellation of the phase noise of the IF signal and the phase noise of second local signal occurs. The resulting output signal has a small level of residual phase noise. In an example presented in said patent, the frequency of the input signal lies in the range from 10 MHz to 2.9 GHz, the frequency of the first local oscillator 209 varies from 505 MHz to 3.395 GHz and the frequency of the second local oscillator 210 equals 3.6 GHz. The frequency of the signal at the output of the BPF 300 equals the sum of the frequencies of the first local oscillator 209 and the second local oscillator 210. When the frequency of the first local oscillator 209 varies from 505 MHz to 3.395 GHz, the frequency of the signal at the output of the BPF 300 is changed from 4.105 GHz to 6.995 GHz. The BPF 300 should pass all frequencies from the mentioned range and suppress the frequencies bellow 4.105 GHz. BPF 201 passes frequencies in the neighborhood of 4.095 GHz. The output signal has a frequency 495 MHz.
The most important reason that prevents the use of the outlined method of the phase noise suppression in a spectrum analyzer, is the appearance of numerous spurious components in the processed signal. In the context of previous example let us suppose that the frequency of the first local oscillator 211 is set up equal to 3.0 GHz (see FIG. 4). The frequency of the second local oscillator 212 is fixed and equal to 3.6 GHz. After mixing in mixer 301 and selection in BPF 300, the true first local signal 208 is created with the frequency 3.0 GHz+3.6 GHz=6.6 GHz. However, due to inevitable non-linearity in the mixer 301, a second harmonic of the first local oscillator signal with the frequency 6.0 GHz appears at the output of the mixer 301 as well. After passing through BPF 300, it appears as a false component of the first local signal 208 at the input of the mixer 200 (FIG. 4c). Since the passband of the BPF 300 inevitably embraces the range 4.105–6.995 GHz, the true component 6.6 GHz cannot be separated from the false one 6.0 GHz by filtering. Let the input signal of the spectrum analyzer have frequency components of 1.9 GHz and 2.505 GHz. The frequency component 2.505 GHz passes the first mixer 200 and the BPF 201, appearing in the first intermediate signal 205 as a component with a frequency 6.6 GHz−2.505 GHz=4.095 GHz. The frequency component 1.9 GHz interacts in the mixer 200 with the second harmonic 6.0 GHz and causes the appearance of the component with the frequency 6.0 GHz−1.9 GHz=4.1 GHz (FIG. 4e). After frequency conversion in the mixer 202 and BPF 203 a true component 0.495 GHz and a false component 0.5 GHz are produced (FIG. 4f). In this way, a by-product satellite that is unavailable in the input signal of the spectrum analyzer appears near the true component. The results of the spectrum measurements become contrary to fact and that cannot be tolerated.
As evidenced by forgoing discussion, a spectrum analyzer that carries out suppression of the phase noise of the local oscillators and, at the same time, does not create spurious responses in the processed signal would be an significant improvement in the art.